Despite our rapidly growing knowledge about the human genome, we do not know all of the genes required for some of the most basic functions of life. To start to fill this gap we developed a high-throughput phenotypic screening platform combining potent gene silencing by RNA interference, time-lapse microscopy and computational image processing. We carried out a genome-wide phenotypic profiling of each of the ,21,000 human protein-coding genes by two-day live imaging of fluorescently labelled chromosomes. Phenotypes were scored quantitatively by computational image processing, which allowed us to identify hundreds of human genes involved in diverse biological functions including cell division, migration and survival. As part of the Mitocheck consortium, this study provides an in-depth analysis of cell division phenotypes and makes the entire high-content data set available as a resource to the community.To target the ,21,000 protein-coding genes in the human genome, we used a chemically synthesized short interfering RNA (siRNA) library designed to uniquely target each gene with 2-3 independent sequences (Supplementary Methods). The siRNAs in this library were tested individually and reduced the messenger RNAs of targeted genes to below 30% of original levels (to an average of 13%) for 97% of more than 1,000 genes tested (Supplementary Table 1). To allow high-throughput phenotyping of each individual siRNA in triplicates by live-cell imaging, we used a previously established workflow for solid-phase transfection using siRNA microarrays coupled to automatic time-lapse microscopy 1 . As a high-content phenotypic assay we chose to monitor fluorescent chromosomes in a human cell line stably expressing core histone 2B tagged with green fluorescent protein (GFP) 1 . After seeding on the siRNA microarrays, on average 67 (630) cells for each siRNA of the library were imaged in triplicates for 2 days, thus documenting many of their basic functions such as cell division, proliferation, survival and migration. Image processing reveals mitotic hitsThis resulted in a large data set of ,190,000 time-lapse movies providing time-resolved records of over 19 million cell divisions. To automatically score and annotate phenotypes in this large data set, we developed a computational pipeline 2 ( Fig. 1) extending previously established methods of morphology recognition by supervised machine learning [3][4][5][6] . In brief, after segmentation, about 200 quantitative features were extracted from each nucleus and used for classification into one of 16 morphological classes ( Fig. 1 and Supplementary Movies 1-30) by a support vector machine classifier previously trained on a set of ,3,000 manually annotated nuclei (Supplementary Methods). This classifier automatically recognizes changes in nuclear morphology due to the cell cycle, cell death or other phenotypic changes with an overall accuracy of 87% (Supplementary Fig. 1) and allows us to convert each time-lapse movie into a phenotypic profile that quantifies the response to each siRNA ...

Genomic abnormalities are often seen in tumor cells, and tetraploidization, which results from failures during cytokinesis, is presumed to be an early step in cancer formation. Here, we report a cell division control mechanism that prevents tetraploidization in human cells with perturbed chromosome segregation. First, we found that Aurora B inactivation promotes completion of cytokinesis by abscission. Chromosome bridges sustained Aurora B activity to posttelophase stages and thereby delayed abscission at stabilized intercellular canals. This was essential to suppress tetraploidization by furrow regression in a pathway further involving the phosphorylation of mitotic kinesin-like protein 1 (Mklp1). We propose that Aurora B is part of a sensor that responds to unsegregated chromatin at the cleavage site. Our study provides evidence that in human cells abscission is coordinated with the completion of chromosome segregation to protect against tetraploidization by furrow regression.

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This paper explores new approaches to the symmetric traveling-salesman problem in which 1-trees, which are a slight variant of spanning trees, play an essential role. A 1-tree is a tree together with an additional vertex connected to the tree by two edges. We observe that (i) a tour is precisely a 1-tree in which each vertex has degree 2, (ii) a minimum 1-tree is easy to compute, and (iii) the transformation on “intercity distances” cij → Cij + πi + πj leaves the traveling-salesman problem invariant but changes the minimum 1-tree. Using these observations, we define an infinite family of lower bounds w(π) on C*, the cost of an optimum tour. We show that maxπw(π) = C* precisely when a certain well-known linear program has an optimal solution in integers. We give a column-generation method and an ascent method for computing maxπw(π), and construct a branch-and-bound method in which the lower bounds w(π) control the search for an optimum tour.

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When vertebrate cells exit mitosis various cellular structures are re-organized to build functional interphase cells 1 . This depends on Cdk1 (cyclin dependent kinase 1) inactivation and subsequent dephosphorylation of its substrates 2-4 . Members of the protein phosphatase 1 and 2A (PP1 and PP2A) families can dephosphorylate Cdk1 substrates in biochemical extracts during mitotic exit 5,6 , but how this relates to postmitotic reassembly of interphase structures in intact cells is not known. Here, we use a live-cell imaging assay and RNAi knockdown to screen a genome-wide library of protein phosphatases for mitotic exit functions in human cells. We identify a trimeric PP2A-B55 complex as a key factor in mitotic spindle breakdown and postmitotic reassembly of the nuclear envelope, Golgi apparatus and decondensed chromatin. Using a chemically induced mitotic exit assay, we find that PP2A-B55 functions downstream of Cdk1 inactivation. PP2A-B55 isolated from mitotic cells had reduced phosphatase activity towards the Cdk1 substrate, histone H1, and was hyper-phosphorylated on all subunits. Mitotic PP2A complexes co-purified with the nuclear transport factor importin-1, and RNAi depletion of importin-1 delayed mitotic

RNA interference (RNAi) is a powerful tool to study gene function in cultured cells. Transfected cell microarrays in principle allow high-throughput phenotypic analysis after gene knockdown by microscopy. But bottlenecks in imaging and data analysis have limited such high-content screens to endpoint assays in fixed cells and determination of global parameters such as viability. Here we have overcome these limitations and developed an automated platform for high-content RNAi screening by time-lapse fluorescence microscopy of live HeLa cells expressing histone-GFP to report on chromosome segregation and structure. We automated all steps, including printing transfection-ready small interfering RNA (siRNA) microarrays, fluorescence imaging and computational phenotyping of digital images, in a high-throughput workflow. We validated this method in a pilot screen assaying cell division and delivered a sensitive, time-resolved phenoprint for each of the 49 endogenous genes we suppressed. This modular platform is scalable and makes the power of time-lapse microscopy available for genome-wide RNAi screens.